Simultaneous Model Selection and Model Calibration for the Proliferation of Tumor and Normal Cells During In Vitro Chemotherapy Experiments

J Comput Biol. 2018 Dec;25(12):1285-1300. doi: 10.1089/cmb.2017.0130. Epub 2018 Sep 22.

Abstract

In vitro experiments were conducted in this work to analyze the proliferation of tumor (DU-145) and normal (macrophage RAW 264.7) cells under the influence of a chemotherapeutic drug (doxorubicin). Approximate Bayesian Computation (ABC) was used to select among four competing models to represent the number of cells and to estimate the model parameters, based on the experimental data. For one case, the selected model was validated in a replicated experiment, through the solution of a state estimation problem with a particle filter algorithm, thus demonstrating the robustness of the ABC procedure used in this work.

Keywords: DU-145 cells; RAW 264.7 cells; approximate Bayesian computation; chemotherapy; state estimation..

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Antineoplastic Agents / pharmacology*
  • Cell Line, Tumor
  • Cell Proliferation / drug effects*
  • Doxorubicin / pharmacology*
  • Drug Resistance, Neoplasm
  • Humans
  • Male
  • Mice
  • Models, Theoretical*
  • Prostatic Neoplasms / pathology*
  • RAW 264.7 Cells

Substances

  • Antineoplastic Agents
  • Doxorubicin